HCIL BBL Speaker Series: Facilitating Affect Regulation Using a Vibrotactile Technology
FACILITATING AFFECT REGULATION USING A VIBROTACTILE TECHNOLOGY
When: Every Thurs during the semester from 12:30p – 1:30p ET
Where: Via Zoom at this same link each week — https://umd.zoom.us/j/92820973827
Dr. Miri will discuss her work on designing vibrotactile technologies to facilitate affect regulation. Specifically, she will cover how she designed, engineered, and evaluated a vibrotactile breathing pacer to help with stress reduction in a population of young college students. She will discuss whether the pacer was effective in anxiety reduction (both in self report and psychophysiology measures) and, where effective for whom it was effective (e.g., for those low on Big Five Openness, the device was more effective). She will then discuss how she built on the knowledge gained from a college student population, and is currently targeting her research for children diagnosed with autism spectrum disorder.
Pardis Miri, PhD, is a postdoctoral fellow at Stanford University, where she is working at the intersection of human computer interaction and affective science. Such research is highly interdisciplinary, and involves computer systems, human-computer interaction, psychology, and behavioral science. She is being advised by Professor Keith Marzullo at the University of Maryland iSchool, whose research is on distributed systems, and by Professor James Gross, whose research underlies much of what we now know about emotion regulation. She is also working with Professor Antonio Hardan of the Stanford School of Medicine, whose research is on children with Autism Spectrum Disorder.
Dr. Miri leads a multidisciplinary research team in the Stanford Psychophysiology Lab (the WEHAB team) aimed at the design, engineering, and evaluation of technologies to help people to successfully manage their emotions, moods, and stress responses. She is interested in both neurotypical and neurodiverse populations. Specifically, her work focuses on using theoretically-grounded and data-driven approaches to engineer end-to-end systems that empower people to regulate their unwanted affective experiences and behaviors in their everyday lives. Then, by running carefully-designed clinical experiments, she examines both the average effect (whether the system was effective in changing affect) and the heterogeneous effect (for whom the system was effective). The results of this research will inform practice about what types of interventions are more useful for what type of trait and state individual differences, and will reduce the use of drugs in personalized mental healthcare. To know more, please visit https://wehab.stanford.edu